چكيده
ABSTRACT
These days, high efficiency, maximum reliability, and security in the design and
operation of power systems are more important than ever before. The difficulties in
constructing new transmission lines due to limits in rights for their paths make it
necessary to utilize the maximum capacity of existing transmission lines. Flexible
alternating current transmission system (FACTS) devices, as modern active and reactive
power compensators, can be considered as viable and feasible options for satisfying the
voltage security constraints in power systems, since their response to perturbations in
urgent circumstances is fast and their performance in normal conditions is flexible.
This investigation attempts to determine the optimum amounts, types, numbers and
locations of thyristor controlled series compensators (TCSCs) and static var compensators
(SVCs) based on a multi-objective function. This is done by considering static voltage
stability enhancement, power loss reduction, and voltage profile improvement as the
allocation objectives; FACTS devices investment cost reduction considers interest rates
simultaneously. Therefore, non-linear multi-objective optimization has been used in this
thesis in an attempt to find a logical and accurate solution to the allocation problem.
Despite previous works, and for approaching a practical solution, an estimated annual load
profile has been considered for calculating power losses and voltage violation. Here, an
approach based on the goal attainment and fuzzy methods, combined with a genetic
algorithm and simulated annealing is used to compromise between contradictory
objectives. This approach prevents the optimization to be trapped in local optimums.
According to the obtained results on both the IEEE 14-Bus and Fars Regional Electric
networks, the implemented method results in the satisfaction of such allocation objectives
as power loss reduction, investment cost reduction, security margin improvement, and
voltage violation alleviation, simultaneously. It is also concluded that the entire investment
of the FACTS devices is paid off and some additional savings is made. Besides, the
optimization procedure in this study has reached the global optimum- solution by passing
a zigzag convergence path and not trapped in a local minimum. Results show that ignoring
different load levels in allocation procedure for a practical power system may even lead to
a wrong planning decision about the optimum structure of these devices.
Keywords: Allocation, Multi-objective Optimization, Heuristic Algorithms, TCSC, SVC.
